Course: STAT 27420
Title: Introduction to Causality with Machine Learning
Instructor(s): Victor Veitch
Teaching Assistant(s): Irina Cristali
Class Schedule: Sec 1: TR 3:30 PM-4:50 PM in Rosenwald 011
Description: This course is an introduction to causal inference. We'll cover the core ideas of causal inference and what distinguishes it from traditional observational modeling. This includes an introduction to some foundational ideas---structural equation models, causal directed acyclic graphs, and the do calculus. The course has a particular emphasis on the estimation of causal effects using machine learning methods.
Prerequisites: [STAT 24500 or STAT 24510 or STAT 27725] with a grade of B or higher or consent of instructor.